Abstract
Accidental falls and reduced mobility are major risk factors in later life. Changes in a person’s mobility patterns can be related with personal well-being and with the frequency of memory lapses and can be used as risk detectors of incipient neuro-degenerative diseases. Thus, developing technologies for fall detection and indoor localization and novel methods for mobility pattern analysis is of utmost importance in e-health. Choosing the right technology is not only a matter of cost and performance, but also a matter of user acceptability and the perceived ease-of-use by the end user. In this paper, we employ an Analytic Hierarchy Process (AHP) to assess the best fit-to-purpose technology for fall detection and user mobility estimation. Our multi-criteria decision making process is based on the survey results collected from 153 elderly volunteers from 5 EU countries and on 10 emerging e-health technologies for fall detection and indoor mobility pattern estimation. Our analysis points out towards a Bluetooth Low Energy wearable solution as the most suitable solution.
| Original language | English |
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| Title of host publication | MOBIHEALTH 2015 |
| Subtitle of host publication | 5th EAI International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies" |
| Place of Publication | London |
| Publisher | ICST |
| Number of pages | 4 |
| ISBN (Electronic) | 978-1-63190-088-4 |
| Publication status | Published - Oct 2015 |
| Publication type | A4 Article in conference proceedings |
| Event | International ICST Conference on Wireless Mobile Communication and Healthcare - Duration: 1 Jan 1900 → … |
Conference
| Conference | International ICST Conference on Wireless Mobile Communication and Healthcare |
|---|---|
| Period | 1/01/00 → … |
Publication forum classification
- Publication forum level 1